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Stokes K, Clark K, Odetade D, Hardy M, Goldberg Oppenheimer P. Advances in lithographic techniques for precision nanostructure fabrication in biomedical applications. DISCOVER NANO 2023; 18:153. [PMID: 38082047 PMCID: PMC10713959 DOI: 10.1186/s11671-023-03938-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/04/2023] [Indexed: 01/31/2024]
Abstract
Nano-fabrication techniques have demonstrated their vital importance in technological innovation. However, low-throughput, high-cost and intrinsic resolution limits pose significant restrictions, it is, therefore, paramount to continue improving existing methods as well as developing new techniques to overcome these challenges. This is particularly applicable within the area of biomedical research, which focuses on sensing, increasingly at the point-of-care, as a way to improve patient outcomes. Within this context, this review focuses on the latest advances in the main emerging patterning methods including the two-photon, stereo, electrohydrodynamic, near-field electrospinning-assisted, magneto, magnetorheological drawing, nanoimprint, capillary force, nanosphere, edge, nano transfer printing and block copolymer lithographic technologies for micro- and nanofabrication. Emerging methods enabling structural and chemical nano fabrication are categorised along with prospective chemical and physical patterning techniques. Established lithographic techniques are briefly outlined and the novel lithographic technologies are compared to these, summarising the specific advantages and shortfalls alongside the current lateral resolution limits and the amenability to mass production, evaluated in terms of process scalability and cost. Particular attention is drawn to the potential breakthrough application areas, predominantly within biomedical studies, laying the platform for the tangible paths towards the adoption of alternative developing lithographic technologies or their combination with the established patterning techniques, which depends on the needs of the end-user including, for instance, tolerance of inherent limits, fidelity and reproducibility.
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Affiliation(s)
- Kate Stokes
- Advanced Nanomaterials Structures and Applications Laboratories, School of Chemical Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Kieran Clark
- Advanced Nanomaterials Structures and Applications Laboratories, School of Chemical Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - David Odetade
- Advanced Nanomaterials Structures and Applications Laboratories, School of Chemical Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Mike Hardy
- School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast, BT9 5DL, UK
- Centre for Quantum Materials and Technology, School of Mathematics and Physics, Queen's University Belfast, Belfast, BT7 1NN, UK
| | - Pola Goldberg Oppenheimer
- Advanced Nanomaterials Structures and Applications Laboratories, School of Chemical Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
- Healthcare Technologies Institute, Institute of Translational Medicine, Mindelsohn Way, Birmingham, B15 2TH, UK.
- Cavendish Laboratory, Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge, CB3 0HE, UK.
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Carthew J, Taylor JBJ, Garcia-Cruz MR, Kiaie N, Voelcker NH, Cadarso VJ, Frith JE. The Bumpy Road to Stem Cell Therapies: Rational Design of Surface Topographies to Dictate Stem Cell Mechanotransduction and Fate. ACS APPLIED MATERIALS & INTERFACES 2022; 14:23066-23101. [PMID: 35192344 DOI: 10.1021/acsami.1c22109] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Cells sense and respond to a variety of physical cues from their surrounding microenvironment, and these are interpreted through mechanotransductive processes to inform their behavior. These mechanisms have particular relevance to stem cells, where control of stem cell proliferation, potency, and differentiation is key to their successful application in regenerative medicine. It is increasingly recognized that surface micro- and nanotopographies influence stem cell behavior and may represent a powerful tool with which to direct the morphology and fate of stem cells. Current progress toward this goal has been driven by combined advances in fabrication technologies and cell biology. Here, the capacity to generate precisely defined micro- and nanoscale topographies has facilitated the studies that provide knowledge of the mechanotransducive processes that govern the cellular response as well as knowledge of the specific features that can drive cells toward a defined differentiation outcome. However, the path forward is not fully defined, and the "bumpy road" that lays ahead must be crossed before the full potential of these approaches can be fully exploited. This review focuses on the challenges and opportunities in applying micro- and nanotopographies to dictate stem cell fate for regenerative medicine. Here, key techniques used to produce topographic features are reviewed, such as photolithography, block copolymer lithography, electron beam lithography, nanoimprint lithography, soft lithography, scanning probe lithography, colloidal lithography, electrospinning, and surface roughening, alongside their advantages and disadvantages. The biological impacts of surface topographies are then discussed, including the current understanding of the mechanotransductive mechanisms by which these cues are interpreted by the cells, as well as the specific effects of surface topographies on cell differentiation and fate. Finally, considerations in translating these technologies and their future prospects are evaluated.
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Affiliation(s)
- James Carthew
- Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Jason B J Taylor
- Mechanical and Aerospace Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Maria R Garcia-Cruz
- Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Nasim Kiaie
- Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - Nicolas H Voelcker
- Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
- Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria 3168, Australia
- Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, Victoria 3052, Australia
- ARC Centre for Cell and Tissue Engineering Technologies, Monash University, Clayton, Victoria 3800, Australia
- CSIRO Manufacturing, Bayview Avenue, Clayton, VIC 3168, Australia
| | - Victor J Cadarso
- Mechanical and Aerospace Engineering, Monash University, Clayton, Victoria 3800, Australia
- Centre to Impact Antimicrobial Resistance, Monash University, Clayton, Victoria 3800, Australia
| | - Jessica E Frith
- Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia
- ARC Centre for Cell and Tissue Engineering Technologies, Monash University, Clayton, Victoria 3800, Australia
- Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria 3800, Australia
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Zhang X, Yang W, Zhang H, Xie M, Duan X. PEDOT:PSS: From conductive polymers to sensors. NANOTECHNOLOGY AND PRECISION ENGINEERING 2021. [DOI: 10.1063/10.0006866] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Xiaoshuang Zhang
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Wentuo Yang
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Hainan Zhang
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Mengying Xie
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
| | - Xuexin Duan
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
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Sun L, Zou H, Sang S. A low-cost and high-efficiency method for four-inch silicon nano-mold by proximity UV exposure. NANOTECHNOLOGY 2021; 33:075303. [PMID: 34507308 DOI: 10.1088/1361-6528/ac25ab] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 09/10/2021] [Indexed: 06/13/2023]
Abstract
Nano-mold is an essential tool for nano-imprinting. However, large-area nano-mold fabrication relies on expensive equipment or complicated processing. Silicon nano-molds were achieved by proximity ultraviolet lithography and reactive ion etching (RIE). By optimizing the parameters in the processes of exposure, development, and RIE, silicon nano-mold with nano-scale ridges were fabricated with high-precision. The achieved minimum width of nano-ridges was 263 nm. This method is capable of fabricating silicon nano-mold covering four-inch wafer, which is simple, efficient and free from costly equipment.
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Affiliation(s)
- Lei Sun
- MicroNano System Research Center, Key Lab of Advanced Transducers and Intelligent Control Systemof the Ministry of Education & College of Information Engineering, Taiyuan University of Technology, Jinzhong, People's Republic of China
| | - Helin Zou
- Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, People's Republic of China
- Key Laboratory for Micro/Nano Technology and Systems of Liaoning Province, Dalian University of Technology, Dalian, People's Republic of China
| | - Shengbo Sang
- MicroNano System Research Center, Key Lab of Advanced Transducers and Intelligent Control Systemof the Ministry of Education & College of Information Engineering, Taiyuan University of Technology, Jinzhong, People's Republic of China
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Guo R, Qi L, Xu L, Liu L, Sun L, Yin Z, Li K, Zou H. Fabrication of 2D silicon nano-mold by side etch lift-off method. NANOTECHNOLOGY 2021; 32:285301. [PMID: 33823500 DOI: 10.1088/1361-6528/abf50e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 04/06/2021] [Indexed: 06/12/2023]
Abstract
Nano-imprint technology is a method of nano-pattern reproduction, has the characteristics of high resolution, high throughput, and low-cost. It can reduce the complexity and cost of the equipment while improving the resolution, which considered a promising industrial production technology. The key to nanoimprinting lies in the mold, and the quality of the mold directly determines the quality of the imprinted graphics. Here, a method for fabricating sub-100 nm concave 2D silicon nano-mold by side etch lift-off is proposed. The effects of different wet etching time and the metal deposition angle on the width of nanochannels were studied. The measurement result of dry etching shows that on the entire 4 inch silicon wafer, the width of the nanochannel varies by 4% and the depth by 2%. The width of the nanochannel between chips varies by 0.7%, and the depth variation is 1%. With this new method, high-precision and large-scale silicon nano-mold can be produced, which has great potential for realizing high-precision and low-cost manufacturing of nano devices.
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Affiliation(s)
- Ran Guo
- Key Laboratory for Micro/Nano Technology and Systems of Liaoning Province, Dalian University of Technology, Dalian 116024, People's Republic of China
| | - Liping Qi
- Department of Biomedical Engineering, Dalian University of Technology, Dalian 116024, People's Republic of China
| | - Liang Xu
- Key Laboratory for Micro/Nano Technology and Systems of Liaoning Province, Dalian University of Technology, Dalian 116024, People's Republic of China
| | - Lingpeng Liu
- Key Laboratory for Micro/Nano Technology and Systems of Liaoning Province, Dalian University of Technology, Dalian 116024, People's Republic of China
| | - Lei Sun
- MicroNano System Research Center, Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education & College of Information Engineering, Taiyuan University of Technology, Jinzhong 030600, People's Republic of China
| | - Zhifu Yin
- School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130012, People's Republic of China
| | - Kehong Li
- Faculty of electronic information and electrical engineering, Dalian University of Technology, People's Republic of China
| | - Helin Zou
- Key Laboratory for Micro/Nano Technology and Systems of Liaoning Province, Dalian University of Technology, Dalian 116024, People's Republic of China
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Investigating the Association between Motor Function, Neuroinflammation, and Recording Metrics in the Performance of Intracortical Microelectrode Implanted in Motor Cortex. MICROMACHINES 2020; 11:mi11090838. [PMID: 32899336 PMCID: PMC7570280 DOI: 10.3390/mi11090838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 08/27/2020] [Accepted: 08/28/2020] [Indexed: 11/26/2022]
Abstract
Long-term reliability of intracortical microelectrodes remains a challenge for increased acceptance and deployment. There are conflicting reports comparing measurements associated with recording quality with postmortem histology, in attempts to better understand failure of intracortical microelectrodes (IMEs). Our group has recently introduced the assessment of motor behavior tasks as another metric to evaluate the effects of IME implantation. We hypothesized that adding the third dimension to our analysis, functional behavior testing, could provide substantial insight on the health of the tissue, success of surgery/implantation, and the long-term performance of the implanted device. Here we present our novel analysis scheme including: (1) the use of numerical formal concept analysis (nFCA) and (2) a regression analysis utilizing modern model/variable selection. The analyses found complimentary relationships between the variables. The histological variables for glial cell activation had associations between each other, as well as the neuronal density around the electrode interface. The neuronal density had associations to the electrophysiological recordings and some of the motor behavior metrics analyzed. The novel analyses presented herein describe a valuable tool that can be utilized to assess and understand relationships between diverse variables being investigated. These models can be applied to a wide range of ongoing investigations utilizing various devices and therapeutics.
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Mahajan S, Hermann JK, Bedell HW, Sharkins JA, Chen L, Chen K, Meade SM, Smith CS, Rayyan J, Feng H, Kim Y, Schiefer MA, Taylor DM, Capadona JR, Ereifej ES. Toward Standardization of Electrophysiology and Computational Tissue Strain in Rodent Intracortical Microelectrode Models. Front Bioeng Biotechnol 2020; 8:416. [PMID: 32457888 PMCID: PMC7225268 DOI: 10.3389/fbioe.2020.00416] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 04/14/2020] [Indexed: 12/26/2022] Open
Abstract
Progress has been made in the field of neural interfacing using both mouse and rat models, yet standardization of these models' interchangeability has yet to be established. The mouse model allows for transgenic, optogenetic, and advanced imaging modalities which can be used to examine the biological impact and failure mechanisms associated with the neural implant itself. The ability to directly compare electrophysiological data between mouse and rat models is crucial for the development and assessment of neural interfaces. The most obvious difference in the two rodent models is size, which raises concern for the role of device-induced tissue strain. Strain exerted on brain tissue by implanted microelectrode arrays is hypothesized to affect long-term recording performance. Therefore, understanding any potential differences in tissue strain caused by differences in the implant to tissue size ratio is crucial for validating the interchangeability of rat and mouse models. Hence, this study is aimed at investigating the electrophysiological variances and predictive device-induced tissue strain. Rat and mouse electrophysiological recordings were collected from implanted animals for eight weeks. A finite element model was utilized to assess the tissue strain from implanted intracortical microelectrodes, taking into account the differences in the depth within the cortex, implantation depth, and electrode geometry between the two models. The rat model demonstrated a larger percentage of channels recording single unit activity and number of units recorded per channel at acute but not chronic time points, relative to the mouse model Additionally, the finite element models also revealed no predictive differences in tissue strain between the two rodent models. Collectively our results show that these two models are comparable after taking into consideration some recommendations to maintain uniform conditions for future studies where direct comparisons of electrophysiological and tissue strain data between the two animal models will be required.
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Affiliation(s)
- Shreya Mahajan
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States
| | - John K. Hermann
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Hillary W. Bedell
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Jonah A. Sharkins
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Lei Chen
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Keying Chen
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Seth M. Meade
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Cara S. Smith
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Jacob Rayyan
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - He Feng
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Youjoung Kim
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Matthew A. Schiefer
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Dawn M. Taylor
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
- Department of Neuroscience, The Cleveland Clinic, Cleveland, OH, United States
| | - Jeffrey R. Capadona
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
| | - Evon S. Ereifej
- Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, United States
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States
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